1. Field
The present disclosure relates generally to data processing systems and more particularly to a system for image production. Still more particularly, the present disclosure relates to a system for on-demand image tile production.
2. Background
Many types of sensors may be used to collect data, which is in turn used to generate images. One type of sensor may be a synthetic-aperture radar (SAR), a type of radar that produces high-resolution imagery by collecting radio frequency energy from a radar system while the platform moves over some distance. Synthetic-aperture radar may use an antenna mounted on a moving platform, such as an aircraft or spacecraft, to illuminate a target area. Numerous echo waveforms received at the different antenna positions are post-processed to resolve the target. SAR data can be visualized by generating image products using a number of different processing techniques. These processing techniques may vary parameters used in the image formation process, such as display mappings and sidelobe control. These techniques may also incorporate phase information to indicate things such as moving targets, or to increase the resolution through super-resolution techniques. SAR data from multiple passes can be combined together through techniques including interferometry to visualize terrain elevation, temporal changes, or track geophysical phenomena.
Image formation is often supported by large datasets used to generate large digital images, whose dimensions may be many thousands of pixels on a side. Analysts may wish to change processing parameters or generate a different image product based on what is observed in the images. To accomplish these changes, the entire dataset is transferred to the analyst, resulting in large data transfers that consume time and bandwidth, requiring the analyst to have sufficient processing power available on a local workstation. Alternatively, the analyst may make re-processing requests back to a server responsible for generating the images, which are time-consuming as well due to the large volumes of data and computational complexity of the algorithms. The entire image is reprocessed for every new product or change in processing parameters.
The analyst may only need to view a small portion or region of the reprocessed image. To limit the amount of data transferred over the network, the image may be logically segmented into discrete rectangular sub regions, referred to as tiles. When an analyst wishes to view a region of an image, only the tiles necessary to cover the desired region need to be transferred. Existing techniques require that the entire image be reprocessed and segmented prior to transferring the needed tiles.
Therefore, it would be advantageous to have a method and apparatus that takes into account one or more of the issues discussed above, as well as possibly other issues.